• Journal of Korean Dental Science
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• v.16 no.1
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• pp.1-8
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• 2023

Dental treatment for the disabled should be a customized that considers the characteristics and degree of cooperation of each disabled patient. There are additional considerations during implant treatment and tooth extraction in disabled patients. Since some brain lesion disorder or cardiac disease patients may be taking antiplatelet or anticoagulant medications, it is necessary to evaluate whether these medications should be discontinued before an invasive procedure. Precautions should be taken for patients with heart valve disease considering the risk of infective endocarditis, especially during invasive dental procedures. Moreover, disabled patients may have difficulty in following instructions and cautions. There are specific considerations for each stage of implant treatment in disabled patients. In the case of patients who are in the pre- or post-transplant state, it is necessary to assess their general condition and oral disease due to the risk of infection. Since disabled patients with various systemic diseases may visit the dental clinic, it is important to understand their characteristics and treatment process in order to flexibly adjust the dental treatment plan accordingly.

• Journal of Ginseng Research
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• v.48 no.2
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• pp.140-148
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• 2024

Synthetic biology approaches offer potential for large-scale and sustainable production of natural products with bioactive potency, including ginsenosides, providing a means to produce novel compounds with enhanced therapeutic properties. Ginseng, known for its non-toxic and potent qualities in traditional medicine, has been used for various medical needs. Ginseng has shown promise for its antioxidant and neuroprotective properties, and it has been used as a potential agent to boost immunity against various infections when used together with other drugs and vaccines. Given the increasing demand for ginsenosides and the challenges associated with traditional extraction methods, synthetic biology holds promise in the development of therapeutics. In this review, we discuss recent developments in microorganism producer engineering and ginsenoside production in microorganisms using synthetic biology approaches.

• Journal of the Korean Geographical Society
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• v.36 no.4
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• pp.458-473
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• 2001

The classified map of geomorphic surfaces is the most basic data for the geomorphological research. Up to recent days, the traditional methods extracting specific geomorphic surfaces are accomplished by analyzing the aerial photographs and topographical maps, and field works. Also it needs a lot of time and expertness. Furthermore it is difficult to gain the aerial photographs in Korea. Since digital maps in Korean Peninsula are almost completed recently, we tried to extract specific surfaces by analyzing the characteristics of marine terraces based on the level of paleoshoreline and slope analysis on the terrace surface using GIS. However, research used GIS was hardly found up to date, therefore many problems are not be solved yet. The aim of this study is to develop the more efficient and objective method for the extraction and classification of specific geomorphic surfaces by using GIS in Gampo-eup, Gyeongju city, Southeastem Coast in Korea, where a lot of traditional research has already accomplished. For this aim, we have designed the process of extracting specific geomorphic surfaces, chosen the factors that was Gyeongiu city, Southeastem Coast in Korea, where a lot of traditional research has already accomplished. For this aim, we have designed the process of extracting specific geomorphic surfaces, chosen the factors that was suitable for classification of specific geomorphic surface, and presented method of setting up optimum criteria of extraction. As last, effectiveness and problems of these methods were investigated through conincidence rate and error rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.137-144
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• 2005

In this paper, the extraction method of the edge histogram directly using wavelet coefficients in the wavelet domain for JPEG2000 images is proposed. MPEG-7 Edge Histogram Descriptor(EHD) extracts edge histogram in the spacial domain. This algorithm has much multiplication and addition for the edge extraction because it needs the decoding processing. However because the proposed algorithm extracts the edge histogram in the wavelet domain, it doesn't need the decoding processing and it decreases multiplication and addition. The Discrete Wavelet Transform(DWT) is a standard transform in JPEG2000. The proposed algorithm uses Le Gall 5/3 filter in JPEG2000 and odd coefficients in LH2 and HL2 sub-band. The edge direction can be decided to use rate of HL2 and LH2 odd coefficients. According to experiments, there is no difference of the efficiency between EHD and the proposed algorithm And the proposed algorithm is much better than EHD for multiplication and addition in the edge extraction of images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.46-54
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• 2006

Recently, the important of a personal identification is increasing according to expansion using each on-line commercial transaction and personal ID-card. Although a personal ID-card embedded RFID(Radio Frequency Identification) tag is gradually increased, the way for a person's identification is deficiency. So we need automatic methods. Because RFID tag is vary small storage capacity of memory, it needs effective feature extraction method to store personal biometrics information. We need new recognition method to compare each feature. In this paper, we studied the face verification system using Hippocampal neuron modeling algorithm which can remodel the hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature vector of the face images very fast. and construct the optimized feature each image. The system is composed of two parts mainly. One is feature extraction using NMF(Non-negative Matrix Factorization) and LDA(Linear Discriminants Analysis) mixture algorithm and the other is hippocampal neuron modeling and recognition simulation experiments confirm the each recognition rate, that are face changes, pose changes and low-level quality image. The results of experiments, we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to the existing method.

• Resources Recycling
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• v.29 no.2
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• pp.62-68
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• 2020

In new millennium, wide-reaching demands for selective catalytic reduction (SCR) catalyst have been increased gradually in new millennium. SCR catalyst can prevent the NO_x emission to protect the environment. In SCR catalyst the main composition of the catalyst is typically TiO₂ (70~80%), WO₃ (7~10%), V₂O₅ (~1%) and others. When the SCR catalysts are used up and disposed to landfills, it is problematic that those should exist in the landfill site permanently due to their extremely low degradability. A new advanced technology needs to be developed primarily to protect environment and then recover the valuable metals. Hydrometallurgical techniques such as leaching and liquid-liquid extraction was designed and developed for the spent SCR catalyst processing. In a first stage, V and W selectively leached from spent SCR catalyst, then both the metals were processed by liquid-liquid extraction process. Various commercial extractants such as D2EHPA, PC 88A, TBP, Cyanex 272, Aliquat 336 were tested for selective extraction of title metals. Scrubbing and stripping studies were tested and optimized for vanadium and tungsten extraction and possible separation. 3^rd phase studies were optimized by using iso-decanol reagent.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.503-508
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• 2010

Recently, the advance of mobile devices has made various services possible beyond simple communication. One of services is the predicting the future path of users and providing the most suitable location based service based on the prediction results. Almost of these prediction methods are based on previous path data. Thus, calculating similarities between current location information and the previous trajectories for path prediction is an important operation. The collected trajectory data have a huge amount of location information generally. These information needs the high computational cost for calculating similarities. For reducing computational cost, the meaningful location based trajectory model approaches are proposed. However, most of the previous researches are considering only the physical information such as stay time and the distance for extracting the meaningful locations. Thus, they will probably ignore the characteristics of users for meaningful location extraction. In this paper, we suggest a meaningful location extracting and trajectory simplification approach considering the stay time, distance, and additionally interaction information of user. The method collects the location information using GPS device and interaction information between the user and the others. Using these data, the proposed method defines the proximity of the people who are related with the user. The system extracts the meaningful locations based on the calculated proximities, stay time and distance. Using the selected meaningful locations the trajectories are simplified. For verifying the usability of the proposed method, we collect the behavioral data of smart phone users. Using these data, we measure the suitability of meaningful location extraction method, and the accuracy of prediction approach based on simplified trajectories. Following these result, we confirmed the usability of proposed method.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.53-53
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• 2022

Modem agricultural production needs to provide sustainable management practices that are eco-friendly and low cost. Plant extracts are a cost-effective and environmentally friendly alternative to synthetic plant growth regulators. This study was therefore carried out to investigate the effects of various plant extracts produced using different extraction methods on the vegetative growth of rice under laboratory and greenhouse conditions. For this study, seventeen plant extracts were made from plant species such as leaves of M. arvense, C. asiatica, M. oleifera, V. radiata, V. unguiculate, P. guajava, A. vera, and A. tuberosum, aboveground plant parts of C. rotundus, M. sativa, and P. frutescens, roots of R. undulatum, tubers of A. sativum, leaves and stems of G. max (cv. Taegwang) as well as rice straw and hulls (cv. Hopyeong). As a test crop, we applied these extracts to rice plants. For the purpose of making our extracts, some plant materials and species were collected in fields and others were purchased from Chonnam Hanyaknonghyup Cooperation (South Korea). Leaves, roots, and aboveground plant parts of plant species were dried, ground, extracted (water, boiling water and ethanol) and fermented. Rice growth promotion effects were determined using plant extracts at 0, 0.05, 0.1, 0.5, and 1% concentrations under petri dish conditions. Seven selected plant extracts were applied to rice seeds with soil drench application or seedling at 3-4 leaf stages with soil and foliar applications under greenhouse conditions. For comparison with extracts, we used urea at 0.6%. Of the 17 water extracts used in this study, 10 extracts reduced rice growth, but the other 7 extracts (P. guajava, A. vera, A. tuberosum, M. sativa, A. sativum, and G. max) increased growth by 40-60% on compared to the control in Petri dish bioassay. Thus, these 7 extracts were selected for further study. Under greenhouse conditions, rice growth also increased by 20-40% when the same 7 extracts were applied to rice seeds using soil drench application. Furthermore, at the 3-4 leaf stage rice growth also increased 30-80% or 30-60% when the same 7 extracts were applied using soil and foliar applications. Overall, the 7 extracts produced higher rates of growth promotion when soil drench application was used than when foliar application was used. In the case of boiling water and ethanol extracts, rice growth increased only 20% in response to both soil drench and foliar application of the same 7 extracts. Rice growth promotion was greater when extracts were produced using water extraction method than boiling water and ethanol extraction methods. Most notably, the 7 water extracts used in this study produced higher rates of growth promotion than urea at 0.6% which is typically used for crop growth promotion. Overall, the 7 water extracts when applied using soil drenching method can be used as effective growth promotors of rice in organic agriculture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4B
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• pp.368-376
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• 2009

Over recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. On the contrary, to preserve the same video quality, SVC(Sealable Video Coding) needs a higher bit-rate than AVC(non-layered Video Coding) due to the coding penalty($10%{\sim}30%$). In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two-user simulation environments. The simulation results show that the channel capacity of SVC is $16{\sim}20%$ smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with a new router using EDE(Extraction Decision Engine) and SVC Extractor to improve network performance. In addition, we compare the SVC environment in the proposed framework with previous research on the same way subject. The proposed network framework shows a channel capacity 50%(maximum) lower than that found in previous research studies.